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A Framework of Deep Optimal Features Selection for Apple Leaf Diseases Recognition

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Computers, Materials & Continua 2023年第4期75卷 697-714页

作者： Samra Rehman Muhammad Attique Khan Majed Alhaisoni ammar Armghan Usman Tariq Fayadh Alenezi Ye Jin Kim Byoungchol Chang Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakakahSaudi Arabia Department of Management Information Systems CoBAPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

Identifying fruit disease manually is time-consuming, expertrequired,and expensive;thus, a computer-based automated system is widelyrequired. Fruit diseases affect not only the quality but also the *** a result, it is possible to detect the disease early on and cure the fruitsusing computer-based techniques. However, computer-based methods faceseveral challenges, including low contrast, a lack of dataset for training amodel, and inappropriate feature extraction for final classification. In thispaper, we proposed an automated framework for detecting apple fruit leafdiseases usingCNNand a hybrid optimization algorithm. Data augmentationis performed initially to balance the selected apple dataset. After that, twopre-trained deep models are fine-tuning and trained using transfer ***, a fusion technique is proposed named Parallel Correlation Threshold(PCT). The fused feature vector is optimized in the next step using a hybridoptimization algorithm. The selected features are finally classified usingmachine learning algorithms. Four different experiments have been carriedout on the augmented Plant Village dataset and yielded the best accuracy of99.8%. The accuracy of the proposed framework is also compared to that ofseveral neural nets, and it outperforms them all.

关键词： Convolutional neural networks deep learning features fusion features optimization classification

Time of surgery and surgeon level in supracondylar humerus fractures in pediatric patients:A retrospective study

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World Journal of Orthopedics 2023年第11期14卷 791-799页

作者： Ibrahim A Albrahim ammar K AlOmran Dalal A Bubshait Yaser Tawfeeq Arwa Alumran Jaffar Alsayigh ammar Abusultan Abdulraheem Altalib Zaid A Alzaid Shayma S Alsubaie Mohammad M Alzahrani Department of Orthopedic College of MedicineImam Abdulrahman Bin Faisal UniversityDammam 34212Saudi Arabia Health Information Management and Technology College of Public HealthImam Abdulrahman Bin Faisal UniversityDammam 34212Saudi Arabia

BACKGROUND Supracondylar humerus fractures account for more than 60%of all elbow fractures and about 1/5 of all pediatric ***,these fractures can be associated with risk of complications including neurovascular injuries,malunions and limb *** exists regarding the effect of time of surgical intervention and/or level of surgeon performing the surgery on outcome of these *** To determine whether time of surgical intervention and/or surgeon level influence the outcomes of surgically managed pediatric supracondylar humerus *** We retrospectively studied 155 pediatric patients presenting with a supracondylar humerus fracture in a level 1 trauma center from January 2006 to December *** data extracted included demographic data,fracture characteristics,surgical data,and follow-up *** collected data was analyzed and P values of<0.05 were considered statistically *** Of the cohort,11%of patients had documented post-operative complications,of which the majority occurred in surgeries performed after day time working hours and in fractures requiring open *** the lowest complication rate was found in surgeries performed by pediatric orthopaedic surgeons,this did not reach statistical *** In pediatric patients undergoing surgery for supracondylar fractures,we found a higher complication rate when surgeries were not performed during working *** level and training had no significant effect on the risk of post-operative complications.

关键词： Supracondylar humerus Fracture Time of surgery Level Complications

Encoder-Decoder Based LSTM Model to Advance User QoE in 360-Degree Video

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Computers, Materials & Continua 2022年第5期71卷 2617-2631页

作者： Muhammad Usman Younus Rabia Shafi ammar Rafiq Muhammad Rizwan Anjum Sharjeel Afridi Abdul Aleem Jamali Zulfiqar Ali Arain Ecole Doctorale Mathematiques InformatiqueTelecommunicationde ToulouseUniversity Paul SabatierToulouse31330France School of Electronics and Information Northwestern Polytechnical UniversityXi’an710129China Department of Computer Science NFC Institute of Engineering and Fertilizer ResearchFaisalabad38000Pakistan Department of Electronic Engineering The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Electrical Engineering Sukkur IBA UniversitySukkur65200Pakistan Department of Electronic Engineering Quaid-e-Awam University of EngineeringScience and Technology(QUEST)Nawabshah67450Pakistan Department of Telecommunication Engineering MUETJamshoro76060Pakistan

The development of multimedia content has resulted in a massiveincrease in network traffic for video streaming. It demands such types ofsolutions that can be addressed to obtain the user’s Quality-of-Experience(QoE). 360-degree videos have already taken up the user’s behavior by ***, the users only focus on the part of 360-degree videos, known as aviewport. Despite the immense hype, 360-degree videos convey a loathsomeside effect about viewport prediction, making viewers feel uncomfortablebecause user viewport needs to be pre-fetched in advance. Ideally, we canminimize the bandwidth consumption if we know what the user motionin advance. Looking into the problem definition, we propose an EncoderDecoder based Long-Short Term Memory (LSTM) model to more accuratelycapture the non-linear relationship between past and future viewport positions. This model takes the transforming data instead of taking the direct inputto predict the future user movement. Then, this prediction model is combinedwith a rate adaptation approach that assigns the bitrates to various tiles for360-degree video frames under a given network capacity. Hence, our proposedwork aims to facilitate improved system performance when QoE parametersare jointly optimized. Some experiments were carried out and compared withexisting work to prove the performance of the proposed model. Last but notleast, the experiments implementation of our proposed work provides highuser’s QoE than its competitors.

关键词： Encoder-decoder based lSTM 360-degree video streaming LSTM QoE viewport prediction

A Particle Swarm Optimization Based Deep Learning Model for Vehicle Classification

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Computer Systems Science & Engineering 2022年第1期40卷 223-235页

作者： Adi Alhudhaif ammar Saeed Talha Imran Muhammad Kamran Ahmed S.Alghamdi Ahmed O.Aseeri Shtwai Alsubai Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Department of Computer Science COMSATS University IslamabadWah Cantt47010Pakistan University of Jeddah College of Computer Science and Engineering Department of CybersecurityJeddah21959Saudi Arabia

Image classification is a core field in the research area of image proces-sing and computer vision in which vehicle classification is a critical *** purpose of vehicle categorization is to formulate a compact system to assist in real-world problems and applications such as security,traffic analysis,and self-driving and autonomous *** recent revolution in the field of machine learning and artificial intelligence has provided an immense amount of support for image processing related problems and has overtaken the conventional,and handcrafted means of solving image analysis *** this paper,a combina-tion of pre-trained CNN GoogleNet and a nature-inspired problem optimization scheme,particle swarm optimization(PSO),was employed for autonomous vehi-cle *** model was trained on a vehicle image dataset obtained from Kaggle that has been suitably *** trained model was classified using several classifiers;however,the Cubic SVM(CSVM)classifier was found to out-perform the others in both time consumption and accuracy(94.8%).The results obtained from empirical evaluations and statistical tests reveal that the model itself has shown to outperform the other related models not only in terms of accu-racy(94.8%)but also in terms of training time(82.7 s)and speed prediction(380 obs/sec).

关键词： Vehicle classification intelligent transport system deep learning constrained machine learning particle swarm optimization CNN GoogleNet

可固化mPEG-PDLLA胶束作为载体的新型吲哚美辛口服给药系统的体外研究(英文)

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药学学报 2011年第8期46卷 997-1003页

作者： ammar Ouahab 沈雁平其能涂家生中国药科大学药剂教研室江苏南京210009

本研究旨在制备吲哚美辛固化聚合物胶束(IND-SPM),并研究其体外释放特性。IND-SPM以交联聚维酮XL-10作为载体,并以聚乙二醇单甲醚?聚乳酸嵌段共聚物(mPEG-PDLLA)作为药物载体,通过溶液吸收法,用旋转蒸发仪蒸发溶剂后制得吲哚美辛固化聚... 详细信息

本研究旨在制备吲哚美辛固化聚合物胶束(IND-SPM),并研究其体外释放特性。IND-SPM以交联聚维酮XL-10作为载体,并以聚乙二醇单甲醚?聚乳酸嵌段共聚物(mPEG-PDLLA)作为药物载体,通过溶液吸收法,用旋转蒸发仪蒸发溶剂后制得吲哚美辛固化聚合物胶束(IND-SPM)。取IND 20 mg,以PBS 250 mL为溶出介质进行体外溶出度实验。结果表明,30 min内吲哚美辛的释放量高于90%(w/w)。DSC,1H NMR和SEM结果证明IND被包裹在mPEG-PDLLA中。随着聚合物的用量的增加,吲哚美辛的溶解度可提高4.6倍。IND-SPM适用于开发成片剂或胶囊剂。

关键词：吲哚美辛固化聚合物胶束难溶性药物体外溶出度

Impact of partial slip condition on mixed convection of nanofluid within lid-driven wavy cavity and solid inner body

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Propulsion and Power Research 2022年第4期11卷 544-564页

作者： ammar I.Alsabery Mohammad H.Yazdi Ali S.Abosinnee Ishak Hashim Evgeny Solomin Refrigeration&Air-conditioning Technical Engineering Department College of Technical EngineeringThe Islamic UniversityNajafIraq New Materials Technology and Processing Research Center Department of Mechanical EngineeringNeyshabur BranchIslamic Azad UniversityNeyshaburIran Altoosi University College NajafIraq Department of Mathematical Sciences Faculty of Science&TechnologyUniversiti Kebangsaan Malaysia43600Bangi SelangorMalaysia Department of Electric Power Generation Stations Network and Supply SystemsInstitute of Engineering and TechnologySouth Ural State University76Lenin AvenueChelyabinsk454080Russian Federation

In thermofluid systems,the lid-driven square chamber plays an imperative role in analyzing thermodynamics’first and second laws in limited volume cases executed by sheer effects with a prominent role in many industrial applications including electronic cooling,heat exchangers,microfluidic components,solar collectors,and renewable ***,nanofluids as working fluids have demonstrated potential for heat transfer enhancement systems,however there are some concerns about irreversibility problems in the *** to this problem and in line with the applications of partial slip on fluid flow modification and irreversibilities,the present study considers laminar mixed convection and entropy generation analysis of aluminum oxide nanofluid inside a lid-driven wavy cavity having an internal conductive solid body in the presence of a partial slip on the upper surface,which to the best of our knowledge,has not been investigated so *** fundamental equations of the current work with the appropriate boundary conditions are first made dimensionless and then solved numerically using the Galerkin weighted residual *** main parameters of the flow and heat transfer,entropy generation,and Bejan number are presented and explained in *** outcomes indicate that the partial slip is more effective when friction irreversibilities govern the *** the presence of slip condition,the flow circulation changes the trend in the middle of the cavity around the solid block leading to a decrease in the isentropic lines at the dense sections with almost 30%less than the case of no-slip *** is concluded that partial slip shows different trends on the local Nusselt number interface along the wavy wall improving the average Nusselt number where high friction irreversibilities dominate.

关键词： Entropy generation Mixed convection Lid-driven wavy cavity Nanofluid Inner cylinder Partial slip

Success Factors of Extracorporeal Shock Wave Lithotripsy (ESWL) for Renal &Ureteric Calculi in Adult

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Open Journal of Urology 2014年第3期4卷 26-32页

作者： ammar Fadil Abid Medical College Al-Mustansirya University Al-Yarmouk Teaching Hospital Baghdad Iraq

The purpose of this study was to define factors that have a significant impact on the stone-free rate after ESWL. Methods: A total of 417 patients harboring renal or ureteral stones underwent extracorporeal shock wave lithotripsy (ESWL) between October 2008 and July 2012. Eighty five patients were lost on follow up. The remaining (n = 332). All patients were >18 yr of age. Siemens and SLX-F2 electromagnetic machines were used to impart shock waves. Patients were stratified according to localization (pelvic, calyceal, or ureteral stones) and stone size (up to 10 mm, 10 - 20 mm, and >20 mm). Result: The overall success rate was 251/332 (75.6%) achieve stone free status. Repeated ESWL sessions were needed in 258 (61.9%). Of eleven variables were studied including age, sex, side, location (pelvic, calyx, ureter), ureteric stent, previous renal surgery, stone size, number of shock waves, opacity of stone, renal system state, and type of lithotripter, three variables were significantly affect the success rate namely stone size, number of shock waves and location of stone. Conclusions: ESWL remains one of the most commonly utilized treatments for patients with upper urinary tract calculi;Stone diameter, location, and number of shock waves, are the most important predictors determining stone clearance after ESWL of renal and ureteric calculi. To optimize treatment outcomes with ESWL the presence of treating urologist is essential to optimize the final result.

关键词： ESWL Renal Stone Ureteric Stone Success Factors

Fast Intra Mode Selection in HEVC Using Statistical Model

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Computers, Materials & Continua 2022年第2期70卷 3903-3918页

作者： Junaid Tariq Ayman Alfalou Amir Ijaz Hashim Ali Imran Ashraf Hameedur Rahman ammar Armghan Inzamam Mashood Saad Rehman Department of Computer Science&Engineering HITEC UniversityTaxilaPakistan L@BISEN Equipe LSLYncrea Oust20 rue Cuirasse BretagneBrest29200France Department of IT and CS Pak-Austria FachhochschuleHaripurPakistan Department of Electrical Engineering Jouf UniversitySakakaKSA

Comprehension algorithms like High Efficiency Video Coding(HEVC)facilitates fast and efficient handling of multimedia *** algorithms involve various computation modules that help to reduce the size of content but preserve the same subjective viewing ***,the brute-force behavior of HEVC is the biggest hurdle in the communication of multimedia ***,a novel method will be presented here to accelerate the encoding process of HEVC by making early intra mode decisions for the ***,the HEVC applies 35 intra modes to every block of the frame and selects the best among them based on the RD-cost(rate-distortion).Firstly,the proposed work utilizes neighboring blocks to extract available information for the current *** this information is converted to the probability that tells which intra mode might be best in the current *** proposed model has a strong foundation as it is based on the probability rule-2 which says that the sum of probabilities of all outcomes should be ***,it is also based on optimal stopping theory(OST).Therefore,the proposed model performs better than many existing OST and classical *** proposed algorithms expedited the encoding process by 30.22%of the HEVC with 1.35%Bjontegaard Delta Bit Rate(BD-BR).

关键词： Statistical HEVC angular mode reduce time

Evolution of microstructural and mechanical properties of AISI 316 during continuous drive friction welding process

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China Welding 2020年第4期29卷 7-12页

作者： ammar Jabbar Hassan Taoufik Boukharouba Djamel Miroud Nacer-Eddine Titouche Salah Ramtani Houari Boumediene University of Sciences and Technology BP.32El-Alia16111 Bab-EzzoaurAlgiersAlgeria Birine Nuclear Research Center BP.180Ain OusseraDjelfa17200Algeria Paris University 13 Galilée Institute93430 VilletaneuseFrance

The aim of present study is introducing a method by subdividing friction welding phases into three steps according to the temperature change during continuous drive friction welding operation. Thermal curve allowable subdividing of the friction welding phase's time into three distinct periods, while the microstructure evolution during friction welding goes through three different situations. The effects of three distinct periods were achieved by macro-microscopy, microhardness HV_(0.1), tensile tests and scanning electronic microscopy(SEM).The results clearly show that the microstructure during the friction phase goes through three completely different situations which mechanically influenced on microstructure, tensile strength and ductility of the welded joint.

关键词： Continuous drive friction welding friction welding phase steps tensile strength microhardness microstructure